I. Field of the Invention
The present invention relates to scheduling transmissions for multiple applications of multiple users from a femtocell base station in a wireless communication system. The scheduling takes the quality-of-service (QoS) requirements of the different applications into account.
II. Description of the Related Art
Scheduling in Wireless Cellular Data Networks
Following the rapid increase of the Internet use and IP-based data applications, wireless systems now support a wide variety of data services as well as voice. Such services have grown very popular, thereby increasing the load on wireless systems. Additionally, the heterogeneity of QoS requirements of these services results in significant difficulties in providing good service.
Wireless systems have utilized the bursty nature of data communication as well as the geographical distribution of its users across a cell to increase the overall spectrum efficiency, as well as peak and average user data rates. This is accomplished by the utilization of multiuser diversity in which data access is provided only to a subset of the active users at a given time based on the regular channel quality feedback received from all users. In multiuser diversity, system resources are used towards sending data to users whose channel qualities are relatively good, thereby increasing the spectrum efficiency. A scheduler is used to decide which users to service at a given time. The sum-rate capacity maximizing scheduler (usually referred to as the Maximum Carrier-to-Interference Ratio (Max C/I) Scheduler) schedules service to the user with the best channel condition at a given time. Coupled with adaptive coding and modulation, the scheduled user is then serviced with the highest possible data rate it can successfully receive during the allotted time. However, this scheduler is unfair as it heavily favors users that are closer to the base station since a closer proximity to the base station results in better channel conditions for such users. Actually, a stationary user near the cell boundary may starve for service if this scheduler is used. There have been numerous efforts in the literature to develop fair schedulers for wireless packet data networks. One such scheduler, the proportional fair (PF) scheduler, as introduced in the U.S. Pat. No. 6,449,490, tries to maintain a balance between the conflicting goals of maintaining a near-optimal network sum-rate capacity and allowing all users a fair access to system resources. The PF scheduler keeps track of the average data rate observed by each active user over a given time period and ranks users relative to the ratio of their potential service data rate (if scheduled) to their average data rate. The top ranked user(s) are then scheduled for service. Mathematically, at a given time n, the PF rule schedules service for user i provided that
                              max          i                ⁢                                            ChC              i                        ⁡                          (              n              )                                                          F              i                        ⁡                          (              n              )                                                          (        1        )            
Here, ChCi(n) is the instantaneous channel condition for user i at time n, Fi(n) is the average channel condition for user i at time n over a pre-specified period of time. The instantaneous channel condition may be either the C/I ratio of the channel, or the corresponding instantaneous achievable transmission data rate for a given packet error rate. Similarly, the average channel condition may be either the average C/I ratio or the average observed data rate for the user in question. The preferred embodiment for the PF rule is to use the ratio of the instantaneous achievable transmission rate to the average observed data rate for each user. This way, a user which observes poor channel conditions most of the time can also get service at times where its relative channel quality with respect to its own average is high. It has been shown that the PF scheduler gives equal system resources to users who only differ in the distance from the base station, their channel fading characteristics being the same. Different variants and generalizations of the PF rule have been proposed as well. For example, U.S. Pat. No. 7,463,631 incorporates a priority function to the PF rule, and U.S. Pat. No. 7,230,991 introduces a so-called “alpha” parameter to the PF rule to adaptively migrate between the Max C/I and PF rules. Similarly, U.S. Pat. No. 7,596,089 defines a generalized PF rule, where user i is scheduled whenever
                              max          i                ⁢                                                            ChC                i                            ⁡                              (                n                )                                                                    F                i                            ⁡                              (                n                )                                              ⁢                                    h              ⁡                              (                                                      ChC                    i                                    ⁡                                      (                    n                    )                                                  )                                                    ChC              i              avg                                                          (        2        )            
Here, ChCiavg is the average achievable data rate, as reported by the user and h(ChCi(n)) is a function of user i's instantaneous achievable data rate at time n if it gets scheduled. The patent describes a number of different such functions which result, in addition to the regular PF rule, new rules where scheduling is conducted such that user throughputs are proportional to the variations of their requested rates.
One documented shortcoming of the PF scheduler has been its inability to ensure queue stability at the base station. In other words, it is possible for the queues to grow without bounds under the PF rule. The exponential scheduler, described in the article “Scheduling for Multiple Flows Sharing a Time-Varying Channel: The Exponential Rule” in the American Mathematical Society Translations introduces an exponential function of the queueing delay for the head-of-line packet destined for each user to remedy this problem. Similarly, U.S. Pat. No. 7,768,973 conducts scheduling for an OFDMA wireless system using a Lagrangian optimization of the proportional fairness term at each time slot using user specific data rate constraints. These constraints in turn, provide a solution to the stability problem of the PF rule.
Most schedulers in the literature have focused their attention on maintaining a good balance between maximizing the sum-rate network capacity and user fairness. However, such algorithms do not attempt to satisfy the heterogeneous quality-of-service (QoS) requirements of the individual users. A few recently proposed scheduling rules remedy this problem by incorporating user specific QoS parameters into the scheduling decision directly. Most common QoS parameters that have been used so far are minimum average data rate, minimum instantaneous data rate, and minimum delay of the user packets to be transmitted.
So far, a number of token-based solutions have been proposed to take the QoS parameters into account. Here, a user specific token counter is introduced which is incremented at every scheduling interval and is decremented whenever the user is scheduled. The amount by which the token count is incremented/decremented is service specific. For example, U.S. Pat. No. 7,298,719 proposes to incorporate into the PF rule a multiplicative exponential token term. Mathematically, at a given time n, this rule schedules service for user i provided that
                              max          i                ⁢                                                            ChC                i                            ⁡                              (                t                )                                                                    F                i                            ⁡                              (                t                )                                              ⁢                      ⅇ                                          α                i                            ⁢                                                T                  i                                ⁡                                  (                  n                  )                                                                                        (        3        )            
Here, Ti(n) is the token count for user i at time n and ai is an adjustable parameter. Therefore in this rule, any user for which the token count from the desired QoS is largest may get scheduled, despite its PF ratio rank since the exponential term would dominate. Similarly, U.S. Pat. No. 7,349,338 proposes a token count that tracks the user's achieved performance relative to a target minimum throughput. This token count is subsequently used in determining which user(s) to service. Additionally, U.S. Pat. No. 7,734,805 describes a user specific Satisfaction Metric and a Dissatisfaction Metric which are incorporated in scheduling decisions. These metrics are in fact two different token counts for each user where the token amount describes the amount of satisfaction/dissatisfaction of each user regarding the QoS of the service it is currently subscribed.
To accommodate for QoS requirements, U.S. Pat. No. 7,463,631 proposes a modification to the PF rule. Here, Fi(n) in (1) is replaced by a term that relates to not the actual average user throughput, but rather the projected user throughput, which is dictated by the user priority and/or QoS requirements.
In all of the above prior art schedulers, each user's data is placed into a user specific buffer. Based on the feedback received from the user on channel quality as well as the fairness criterion, the base station decides which user(s) to service at a given time instance. In this set up, a limited QoS support may be possible since associated with each user's head of buffer packet, a QoS parameter may exist. A scheduler may incorporate this QoS parameter in its decision making as well. While service differentiation across different users may be possible this way, differentiation amongst various applications of a given user is still not possible.
Wireless Femtocell Networks
In cellular networks, it is known that a significant percentage of the calls and the majority of the data services are requested when the user is indoors. Then, it is extremely important for mobile operators to provide good indoor coverage for both voice and data.
The traditional approach to providing indoor coverage is to use the outdoor macrocells. Here each base station location, transmit power as well antenna configuration are set so that coverage in the cell, both outdoors and indoors, is acceptable. While this approach is the current solution, it has a number of serious drawbacks. For one, it is very expensive to use an outside-in approach for indoor coverage. This is because, especially for the radio frequencies of 3G, LTE and beyond, the signal attenuation is dramatically high when it goes through the building walls. Therefore, an indoor user, for the same grade of service, will require a much higher power allocation from the base station compared to an outdoor user. This is return, results in a much lower cell throughput, as less power is left for the provision of service to other users. Second, higher data rates in 3G, LTE and beyond are possible via the use of high order modulation and coding, which in return, require high, observed channel qualities. An indoor user, due to the above mentioned penetration losses, is more unlikely to observe such channel qualities. Therefore, provisioning multimedia services that require stringent QoS requirements is less likely indoors.
To alleviate these shortcomings, a solution that involves an indoor unit serving indoor users has been proposed. Femtocells, also known as home base stations are developed as cellular network access points that connect regular mobile users to a cellular operator's network over the Internet, using residential DSL, cable, broadband connections, optical fibres or wireless last-mile solutions.
The femtocell unit incorporates the functionality of a typical base station and also a radio network controller. It is connected to the cellular operator's core network via the Internet. Femtocells are envisioned to be consumer devices and as such may be self-deployed by users rather than operators. In order to generate minimum interference to outdoor macrocells and neighboring femtocells, a femtocell base station must be able to configure itself automatically.
Conventionally, femtocell base stations are configured to treat users in one of two ways. In the first configuration, the femtocell base station acts as an extension to the existing macrocellular network and provides enhanced network coverage and capacity for all users in range of the femtocell base station. In a residential context, this means that the femtocell base station will provide access to the network for those resident in that location, as well as for neighbors and passers-by if the macrocellular coverage is poor. In this configuration, all users are considered to be part of an open subscriber group, and the use of the femtocell base station is not restricted to any particular set of users. This configuration is usually referred to as a “open access femtocell.” In the second configuration, the femtocell base station restricts access to the network to a defined set of subscribers. This configuration is usually referred to as a “closed access femtocell.” A hybrid configuration is also possible.
QoS Cognizant Femtocells
An indoor user connected to the cellular operator's network via a femtocell is much more likely to request multiple, parallel data services, each potentially requiring different QoS constraints. The cellular operator needs to satisfy such demands.
As described above, the current “outside-in” approach in 3G, LTE, WiMaX and beyond, makes use of a user-based scheduler for the provision of data to users. A number of the QoS-sensitive scheduling rules that have appeared in the literature have been summarized above. It should be noted here that all of the scheduling rules that have been described so far have been user-based. In other words, the goal has been to equitably, fairly divide the system resources amongst users via a scheduler so that system throughput is as high as possible and, for some schedulers, user-specific QoS constraints are taken into account. This approach is understandable. For one, the fundamental theory behind making high data rates in cellular networks a reality has been the use of multi-user diversity. This idea makes use of the user geographic variation in a typically kilometer-radius cell as well as the channel quality variation in time. By allowing a bursty transmission of data, multi-user diversity achieves high data rates on the average. Second, a typical cellular user is mobile, and the likelihood of such a user to request multiple, parallel data services may not be very high.
However, the scenario is dramatically different for an indoor user. When a femtocell is deployed indoors, its coverage area is much smaller in radius than a outdoor cell. Additionally, the typical number of users connected to a femtocell base station at a given time is likely to be much lower than those connected to a macrocell base station. Furthermore, these fewer users are much more likely to demand multiple, parallel data services at a given time. In this scenario, a different resource allocation scheduling needs to be developed for a femtocell base station.
When multiple applications are active for a given user, the prior art schedulers do not attempt to differentiate between them. The incoming traffic to the base station destined for the users is simply queued in user-specific buffers as they arrive, even if they belong to different applications. If the prior art scheduler uses a QoS-aware rule, for a given user, a single QoS level is set, and all incoming traffic for this user is treated according to this level. When a good percentage of the users have multiple active applications with differing QoS requirements, the user based prior art schedulers may become inefficient. If for example, a user has an active streaming video application as well as an active download application that downloads a large file, the QoS level for this user will be set by the system based on either of these applications. If the setting is according to the video streaming application, then the user will impose a very large burden on the system since the incoming traffic for this user, which is a sum of the streaming video packets and the download file packets, will be treated as if they are all delay and jitter sensitive and have a pre-set minimum average data rate. This, in turn, will unfairly steal system resources from other users that have less stringent QoS requirements. If, on the other hand, the setting is according to the download application, the streaming video application will most likely be experienced at an unacceptable quality level. Since femtocell users have very low, if any, mobility, and are consequently likely to have multiple active applications running, some, but not all which are QoS sensitive, the prior art schedulers will not be very suitable for a femtocell base station.
To our knowledge, there has been no prior art in a scheduler design for a femtocell base station.